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At least 1,171 records · Page 65

Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows

The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.

high pressure reverse osmosis↗

Evaluating proxy influence in assimilated paleoclimate reconstructions – Testing the exchangeability of two ensembles of spatial processes

Climate field reconstructions (CFR) attempt to estimate spatiotemporal fields of climate variables in the past using climate proxies such as tree rings, ice cores, and corals. Data Assimilation (DA) methods are a recent and promising new means of deriving CFRs that optimally fuse climate proxies with climate model output. Despite the growing application of DA-based CFRs, little is understood about how much the assimilated proxies change the statistical properties of the climate model data. To address this question, we propose a robust and computationally efficient method, based on functional data depth, to evaluate differences in the distributions of two spatiotemporal processes. In this study, we apply our test to study global and regional proxy influence in DA-based CFRs by comparing the background and analysis states, which are treated as two samples of spatiotemporal fields. We find that the analysis states are significantly altered from the climate-model-based background states due to the assimilation of proxies. Moreover, the difference between the analysis and background states increases with the number of proxies, even in regions far beyond proxy collection sites. Our approach allows us to characterize the added value of proxies, indicating where and when the analysis states are distinct from the background states.

54 ENVIRONMENTAL SCIENCES↗

Impacts of the Conductive Networks on Solid‐State Battery Operation

The micromorphology of composite cathodes is known to play a vital role in determining all-solid-state battery (ASSB) performance. However, much of our current understanding is derived from empirical observations, lacking a deeper mechanistic foundation. The “rocking chair” concept of battery chemistry requires maintaining charge neutrality, emphasizing the necessity of examining electrode micromorphology from the perspective of conductive networks. This study systematically investigates the microscopic electrochemical impacts of conductive network micromorphology by varying the Li + -to-e − channel ratio in cathodes comprising LiNbO 3 -coated LiNi 0.8 Co 0.1 Mn 0.1 O 2 , Li 6 PS 5 Cl, and carbon fibers. Utilizing multiscale synchrotron-based spectro-microscopy, we unravel that unbalanced Li + and e − conducting channels intensify charge polarization within active cathode particles and accelerate their degradation. A further model system with X-ray nano-tomography resolved e − and Li + channels indicates that spatially uniform and well-paired Li + and e − conducting channels are highly desirable as they could promote more uniform lithiation/delithiation, mitigating microscopic electrochemical polarization. Electrode-scale X-ray holotomography analysis reveals that the impact of conductive networks is particle-size-dependent, with smaller cathode particles being more significantly affected. These findings provide mechanistic insights into the interplay between conductive networks and all-solid-state battery operation, laying the groundwork for rational design and optimization of cathode architectures in future solid-state battery technologies.

36 MATERIALS SCIENCE↗

Local conservation of energy in fully implicit PIC algorithms

We consider the issue of strict, fully discrete local energy conservation for a whole class of fully implicit local-charge- and global-energy-conserving particle-in-cell (PIC) algorithms. Earlier studies demonstrated these algorithms feature strict global energy conservation. However, whether a local energy conservation theorem exists (in which the local energy update is governed by a flux balance equation at every mesh cell) for these schemes is unclear. In this study, we show that a local energy conservation theorem indeed exists. We begin our analysis with the 1D electrostatic PIC model without orbit-averaging, and then generalize our conclusions to account for orbit averaging, multiple dimensions, and electromagnetic models (Darwin). In all cases, a temporally, spatially, and particle-discrete local energy conservation theorem is shown to exist, proving that these formulations (as originally proposed in the literature), in addition to being locally charge conserving and globally energy conserving, are strictly locally energy conserving as well. In contrast to earlier proofs of local conservation in the literature, which only considered continuum time, our result is valid for the fully implicit time-discrete version of all models considered, including important features such as orbit averaging. We demonstrate the local-energy-conservation property numerically with a paradigmatic numerical example.

97 MATHEMATICS AND COMPUTING↗

Using In Situ High-Energy X-ray Diffraction to Quantify Electrode Behavior of Li-Ion Batteries from Extreme Fast Charging

Extreme fast charging (XFC, =15 min charging time) of Li-ion batteries (LIBs) has been proposed as an immediate target to increase the commercial appeal of electric vehicles. However, XFC of LIBs is associated with the degradation of battery performance and safety concerns. Quantitative and simultaneous characterization of various components during cell degradation represents a major experimental challenge. In this work, we outline a methodology for the use of spatially resolved, high-energy X-ray diffraction as a quantitative, in situ method of mapping the degradation of LIBs. We use this approach to study the battery cell capacity loss, both locally (mm scale) and globally over the entire cell (cm scale). Specifically, our workflow allows us to quantify the total amount of plated Li on the anode, as well as its spatial correlation to the structural properties of the anode and cathode. The method complements existing optical methods to resolve the spatial heterogeneity of local degradation mechanisms such as Li plating and provides simultaneous insights into concomitant anode state-of-charge variability. We apply it to commercially relevant single-layer pouch cells with the graphite anode and the LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode. Our results show that Li plating occurs heterogeneously on the graphite anode and that it is spatially correlated to the extent of anode lithiation. In this work, we anticipate that the described workflow will allow for understanding multiscale degradation in energy-storage devices beyond LIBs, where quantitative analysis at a local and global length scale can be performed without the necessity to tear down the device, due to the applicability of high-energy X-rays to probe in situ degradation.

25 ENERGY STORAGE↗

Measurements of the imploding plasma sheath in triple-nozzle gas-puff z pinches

Gas-puff z-pinch implosions are characterized by the formation of a dense annular plasma shell, the sheath, that is driven to the axis by magnetic forces and therefore subject to the magneto-Rayleigh–Taylor instability. Here, the conditions within these sheaths are measured on the 1-MA COBRA generator at Cornell University for various gas species and initial fill densities. The gas-puff loads are initialized by a 7 cm diameter triple-nozzle gas valve assembly with concentric outer and inner annular nozzles and a central gas jet. Thomson scattering and laser interferometry provide spatially resolved flow, temperature, and electron density profiles midway through the implosion, while extreme ultraviolet pinhole cameras record the evolution of the plasma column and photoconducting diodes measure x-ray emission. Analysis of the scattering spectra includes a means of discriminating between thermal and non-thermal broadening to test for the presence of hydrodynamic turbulence. Two types of sheath profiles are observed, those with sharp discontinuities at the leading edge and those with smooth gradients. In both cases, non-thermal broadening is generally peaked at the front of the sheath and exhibits a characteristic decay length that roughly scales with the sheath ion mean free path. Here, we demonstrate that this non-thermal broadening term is inconsistent with laminar velocity gradients and is more consistent with dissipative turbulence driven by unstable plasma waves in a collisionless shock. The resulting differences in sheath profile are then set by the sheath ion collisionality in a manner consistent with recent 1D kinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Lost alpha Faraday cup foil noise characterization during Joint European Torus plasma post-processing analysis

Capacitive plasma pickup is a well-known and difficult problem for plasma-facing edge diagnostics. This problem must be addressed to ensure an accurate and robust interpretation of the real signal measurements vs noise. The Faraday cup fast ion loss detector array of the Joint European Torus (JET) is particularly prone to this issue and can be used as a testbed to prototype solutions. The issue of separation and distinction between warranted fast ion signal and electromagnetic plasma noise has traditionally been solved with hardware modifications, but a more versatile post-processing approach is of great interest. This work presents post-processing techniques to characterize the signal noise. While hardware changes and advancements may be limited, the combination with post-processing procedures allows for more rapid and robust analysis of measurements. The characterization of plasma pickup noise is examined for alpha losses in a discharge from JET’s tritium campaign. In addition to highlighting the post-processing methodology, the spatial sensitivity of the detector array is also examined, which presents significant advantages for the physical interpretation of fast ion losses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Full 3D Kinetic Modeling and Quantification of Positive Streamer Evolution in an Azimuthally Swept Pin-to-Plane Wedge Geometry

Cathode-directed streamer evolution in near atmospheric air is modeled in 3D pin-to-plane geometries using a 3D kinetic Particle-In-Cell (PIC) code that simulates particle-particle collisions via the Direct Simulation Monte Carlo (DSMC) method. Due to the computational challenges associated with a complete 360° volumetric domain, a practical alternative was achieved using a wedge domain and a range of azimuthal angles was explored (5°, 15°, 30°, and 45°) to study possible effects on the streamer growth and propagation due to the finite wedge angle. A DC voltage of 6 kV is administered to a hemispherical anode of radius 100 μm, with a planar cathode held at ground potential, generating an over-volted state with an electric field of 4 MV/m across a 1500 μm gap. The domain is seeded with an initial ion and electron density of 10 18 m -3 at 1 eV temperature confined to a spherical region of radius 100 μm centered at the tip of the anode. The air chemistry model [1] includes standard Townsend breakdown mechanisms (electron-neutral elastic, excitation, ionization, attachment, and detachment collision chemistry and secondary electron emission) as well as streamer mechanisms (photoionization and ion-neutral collisions) via tracking excited state neutrals which can then either quench via collisions or spontaneously emit a photon based on specific Einstein-A coefficients [2, 3]. In this work, positive streamer dynamics are formally quantified for each wedge angle in terms of electron velocity and density as temporal functions of coordinates r, Φ, and z. Applying a random plasma seed for each simulation, particles of interest are tracked with near femtosecond temporal resolution out to 1.4 ns and spatially binned. This process is repeated six times and results are averaged. Prior 2D studies have shown that the reduced electric field, E/n, can significantly impact streamer evolution [4]. We extend the analysis to 3D wedge geometries, to limit computational costs, and examine the wedge angle’s effect on streamer branching, propagation, and velocity. Results indicate that the smallest wedge angle that produced an acceptably converged solution is 30°. The potential effects that a mesh, when under-resolved with respect to the Debye length, can impart on streamer dynamics and numerical heating were not investigated, and we explicitly state here that the smallest cell size was approximately 10 times the minimum λ D in the streamer channel at late times. This constraint on cell size was the result of computational limitations on total mesh count.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis

Accurate and timely forecasts of CO 2 plume distribution throughout the injection and post-injection phases are crucial for detecting plume migration, assessing leakage risks, and supporting operational decisions in geologic carbon storage (GCS). Current convolutional neural network-based approaches primarily focus on spatial information and overlook temporal dependencies in plume distributions, thus limiting their ability to capture dynamic movement effects and provide accurate predictions of plume migration. In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED)-ConvLSTM, each uniquely designed to capture both spatial and temporal features. We apply the proposed methods to forecast the dynamic distribution of CO 2 plumes based on 108 reservoir simulations over a 30-year injection and a 30-year post-injection period. The results indicate that the ED-ConvLSTM model outperforms the AE-LSTM model in accurately predicting the spatiotemporal dynamics of CO 2 plume migration, achieving R 2 values above 0.99. To provide a deeper understanding of these model predictions, we employ a gradient-based explanation method on the trained models. This approach provides insights into the influence of input variables on plume migration forecasts and uncovers the underlying prediction mechanisms of the proposed models. Furthermore, we introduce a transfer learning technique, enabling fast and accurate plume migration forecasting in the post-injection phase by leveraging the trained model during the injection phase. This reduces the necessity for extensive data collection or re-training. In conclusion, the methods proposed in our work enhances the performance and interpretability of CO 2 plume migration forecasts, thereby facilitating informed decision-making throughout the entire lifecycle of GCS applications.

58 GEOSCIENCES↗

Correlating Nanoscale Secondary Ion Mass Spectrometry and Atom Probe Tomography Analysis of Uranium Enrichment in Metallic Nuclear Fuel

Distribution and enrichment of 235U within nuclear fuels are essential to material performance and reactor safety. With the development of metallic U fuels, understanding 235U homogeneity has become increasingly important, however, it is difficult to map with high spatial, and mass resolution to analyze both matrix and secondary phase precipitates. Here, we analyze 235U enrichment in matrix and carbide phases in LEU-Mo via two chemical imaging modalities: nanoscale secondary ion mass spectrometry (nanoSIMS) and atom probe tomography (APT). NanoSIMS and APT provided consistent results, with no statistically significant difference between measured and nominal enrichment (19.75 % 235U).

U-10Mo, atom probe tomography, nanoscale secondary↗

Development and Analysis of Optimal Multilevel Solvers on Advanced Computers. Final Report

Constrained optimization in the context of time dependent, partial differential equations (PDE) leads to a symmetric, block-tridiagonal system of nonlinear equations that must be solved repeatedly in an iterative solution strategy. The blocks represent spatial discretization, while the connection between the blocks represents a forward and backward integration in time. The focus of this project is to apply a parallel-in-time (PiT) solution technique to the large block-triangular system.

97 MATHEMATICS AND COMPUTING↗

Accelerated Stress Testing of Perovskite Photovoltaic Modules: Differentiating Degradation Modes with Electroluminescence Imaging

Herein, electroluminescence (EL) and thermal imaging are used to examine p–i–n metal halide perovskite (MHP) photovoltaic (PV) mini-modules (MA0.6FA0.4PbI3, 20 cells, 78 cm2) before and after indoor-accelerated stress testing or outdoor deployment. Distinct spatial patterns in the EL images emerge, which depend on the external stress conditions experienced by the mini-module. Imaging results highlight a distribution of dark speckle features that dominate after UV stress, attributed to widespread interfacial contact degradation. Lateral intensity gradients across cells dominate after thermal cycling (TC) stress, attributed to current crowding near scribe defects. While current–voltage analysis alone does not give full insight on the degradation process, this study shows that distinct degradation modes can be further defined by multimodal electro-optical imaging (i.e., EL combined with photoluminescence and dark lock-in thermography). Neither UV exposure nor TC-accelerated stress testing alone replicates the same degradation signatures observed after outdoor deployment, suggesting that multiple degradation modes occur under concurrent stressors outdoors. Finally, spatial characterization of degradation modes in MHP PV mini-modules before and after accelerated stress testing lays the groundwork for developing targeted accelerated stress testing procedures through comparison with outdoor aging.

14 SOLAR ENERGY↗

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

Seismoacoustic Analysis of the Large Surface Explosion Coupling Experiment Using a Large- N Seismic Array

Seismoacoustic signals at local distance (<~10 km) are widely used as important constraints on source parameters for near-surface events, yet the seismoacoustic wave generation and energy partitioning are not fully understood. Spatially dense sensors could provide observations in high resolution to capture the full wavefield for better understanding wave propagation and improving source estimation. Recently, spatially dense observations of the local seismoacoustic wavefield produced by a pair of 1-ton surface explosions have been recorded using a large-N seismic array. This large-N array consists of 446 geophones and covers an area of approximately 2×2.5 km 2 . The two surface explosions occur at the same location but at different times with different atmospheric conditions. Both seismic and air–ground coupled acoustic waves from the two surface explosions are well observed. Analyses of signals recorded by the large-N seismic array show different acoustic wave speed and amplitude for the two explosions. A strong spatial variability in acoustic wave speed and amplitude for each explosion is also observed. Finally, the observations suggest the important role of local atmosphere state on wave propagation and source estimation and demonstrate how the use of a large-N capability can improve characterization of the propagation medium and source.

58 GEOSCIENCES↗

Observationally constrained analysis of sulfur cycle in the marine atmosphere with NASA ATom measurements and AeroCom model simulations

The atmospheric sulfur cycle plays a key role in air quality, climate, and ecosystems, such as pollution, radiative forcing, new particle formation, and acid rain. In this study, we compare the spatially and temporally resolved measurements from the NASA Atmospheric Tomography (ATom) mission with simulations from five AeroCom III models for four sulfur species (dimethyl sulfide (DMS), sulfur dioxide (SO 2 ), particulate methanesulfonate (MSA), and particulate sulfate (SO 4 )). We focus on remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~12 km altitude range covering all four seasons. In general, the differences among model results can be greater than 1 order of magnitude. Comparing with observations, model-simulated SO 2 is generally low, whereas SO 4 is generally high. Simulated DMS concentrations near the sea surface exceed observed levels by a factor of 5 in most cases, suggesting potential overestimation of DMS emissions in all models. With GEOS model simulations of tagging emission from anthropogenic, biomass burning, volcanic, and oceanic sources, we find that anthropogenic emissions are the dominant source of sulfate aerosol (40 %–60 % of the total amount) in the ATom measurements at almost all altitudes, followed by volcanic emissions (18 %–32 %) and oceanic sources (16 %–32 %). Similar source contributions can also be derived at broad ocean basins and on monthly scales, indicating the representativeness of ATom measurements for global ocean. Our work presents the first assessment of AeroCom sulfur study using ATom measurements, providing directions for improving sulfate simulations, which remain the largest uncertainty in radiative forcing estimates in aerosol climate models.

54 ENVIRONMENTAL SCIENCES↗

3D analysis of abnormal grain growth in calcia doped alumina in the presence of large pores

Abnormal grain growth has been previously found to increase with the inclusion of large pores (∼60 µm in diameter) in 80 ppm calcium doped alumina. However, the two-dimensional analysis could not accurately describe the proximity of the abnormal grains and pores to establish a correlation. This study uses laboratory-based diffraction contrast tomography and x-ray computed tomography to spatially map the pores and abnormal grains in 3D. A preference towards the formation of abnormal grains near large pores is found when compared to all potential sites. This finding supports that the pores may be a nucleation site for complexion transitions that promote abnormal grain growth. The growth of the abnormal grains in a subsequent heat treatment at 1600°C for 16 hrs was also studied. The elongation along the principal axes is similar for both small and large grains, again supporting that abnormal grain growth was facilitated by a complexion transition.

Abnormal grain growth↗

Improving the characterization of fusion in a MuSIC detector by spatial localization

Multi-Sampling Ionization Chambers (MuSIC) provide an efficient means of measuring nuclear reactions with low beam rates (< 10 6 pps). However, in comparison to thin-target measurements, prior measurements using MuSIC detectors all manifest fusion excitation functions with wide error bars in the energy dimension. This uncertainty limits the applicability of these devices in measuring near and sub-barrier fusion cross-sections. Key to overcoming this limitation is spatial localization of the fusion in the detector. By comparing the measured ionization in the MuSIC detector with accurate energy loss calculations the position of the fusion in the detector is determined. The analysis not only provides the desired improvement in energy resolution, but it also allows extraction of the atomic number of the evaporation residues following fusion. Furthermore, the effectiveness of this approach is demonstrated for 18 O+ 12 C measured with MuSIC@Indiana.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗